Use case 1
Ticket triage
Classifies, prioritizes, routes, and drafts first responses for human approval.
For Heads of CX, support leaders, ops leaders
05
Closed-loop AI for customer experience and support teams.
Across healthcare ops, SaaS, and services: triage faster, score smarter, and turn every ticket into a learning signal.
01
The work that is quietly eating margin.
An AI support operations layer that triages, summarizes, scores, and learns.
1Volume is up and headcount is flat
2QA samples 2% of tickets
3Knowledge lives in too many tools
4The same escalation repeats all quarter
5Human agents handle work AI should handle
02
The closed-loop system OpenNash builds.
Same operating pattern, tuned to CX and Support workflows.
01 Intake
Capture
Read work from the tools your team already uses.
02 Reason
Decide
Classify, retrieve context, choose the workflow, and flag risk.
03 Draft
Produce
Create the response, report, memo, update, or work product.
04 Approve
Control
Route judgment-heavy or sensitive actions through human review.
05 Learn
Improve
Measure outcomes, exceptions, quality, and cycle time.
Feedback loop: every completed workflow becomes a signal for the next version.
03
High-leverage use cases.
Start where the volume, pain, and business value overlap.
Use case 2
Call and chat summarization
Summarizes, tags, and indexes every interaction.
Use case 3
Knowledge base agent
Answers agent questions from your real KB, policies, and procedures.
Use case 4
QA scoring at 100%
Scores every interaction against your rubric and samples for calibration.
Use case 5
Escalation prediction
Flags conversations likely to escalate before they do.
Use case 6
Agent assist copilot
Provides real-time suggestions, drafts, and policy lookups in the existing console.
04
Before and after.
Representative outcomes depend on scope, data quality, systems, and volume.
Before
Manual drag
- First response in hours
- QA is a tiny sample
- Each agent is an island
- Escalations surprise leadership
to
After
AI-enabled ops
- First response in minutes
- QA on 100% of contacts
- Every agent has a copilot
- Escalations predicted, not discovered
First-response time
-60%
Representative range
QA coverage
100%
Representative range
AHT
-25%
Representative range
CSAT
+8-12 pts
Representative range
Next step
Build your AI support operations layer.
Book a 30-minute meeting or email [email protected] with the workflow that hurts, the tools involved, and what success would look like in 90 days.